code: def parse_args():
      parser = argparse.ArgumentParser(
          description="Simple example of training script."
      )
  
      parser.add_argument(
          "--output-path",
          type=str,
          help="Path to output directory. Defaults to the orginal checkpoint directory.",
          required=True,
      )
  
      parser.add_argument(
          "--model-name",
          required=True,
          type=str,
          help="7b, 13b or 70b.",
      )
  
      parser.add_argument(
          "--checkpoint",
          type=str,
          required=True,
          help="Path to checkpoint containing the LoRA weights.",
      )
  
      args = parser.parse_args()
  
      return args
  
file_path: ray/doc/source/templates/04_finetuning_llms_with_deepspeed/merge_lora_weights.py
imports: import torch
  import argparse
  import time
  import peft
  from pathlib import Path
  from transformers import AutoModelForCausalLM, AutoTokenizer, StoppingCriteriaList
  from utils import download_model, get_mirror_link, get_checkpoint_and_refs_dir
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: args